{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "754def73",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c6476681",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>时间</th>\n",
       "      <th>基站编号</th>\n",
       "      <th>小区编号</th>\n",
       "      <th>本地小区标识</th>\n",
       "      <th>上行可用的PRB个数</th>\n",
       "      <th>下行可用的PRB个数</th>\n",
       "      <th>上行PhysicalResourceBlock被使用的平均个数</th>\n",
       "      <th>下行PhysicalResourceBlock被使用的平均个数</th>\n",
       "      <th>上行PUSCH的PhysicalResourceBlock被使用的平均个数</th>\n",
       "      <th>小区内的平均用户数</th>\n",
       "      <th>...</th>\n",
       "      <th>用户随机接入时TA值在区间11范围的接入次数</th>\n",
       "      <th>MR测量上报RSRP在Index0区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index1区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index2区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index3区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index4区间的次数</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU上行丢弃的总包数包</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU上行期望收到的总包数</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019014</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>6.4553</td>\n",
       "      <td>31.5065</td>\n",
       "      <td>2.1503</td>\n",
       "      <td>22.6341</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>178</td>\n",
       "      <td>9943</td>\n",
       "      <td>0</td>\n",
       "      <td>2218</td>\n",
       "      <td>0</td>\n",
       "      <td>2179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019015</td>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>8.8281</td>\n",
       "      <td>21.5452</td>\n",
       "      <td>4.2220</td>\n",
       "      <td>19.1064</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>180</td>\n",
       "      <td>8427</td>\n",
       "      <td>0</td>\n",
       "      <td>1510</td>\n",
       "      <td>0</td>\n",
       "      <td>1423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019016</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>5.5024</td>\n",
       "      <td>11.9276</td>\n",
       "      <td>1.8618</td>\n",
       "      <td>15.4729</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>48</td>\n",
       "      <td>575</td>\n",
       "      <td>6371</td>\n",
       "      <td>0</td>\n",
       "      <td>2030</td>\n",
       "      <td>0</td>\n",
       "      <td>1919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019023</td>\n",
       "      <td>3</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>3.1113</td>\n",
       "      <td>0.9637</td>\n",
       "      <td>0.0077</td>\n",
       "      <td>0.0509</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019024</td>\n",
       "      <td>4</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>2.6004</td>\n",
       "      <td>1.0051</td>\n",
       "      <td>0.1201</td>\n",
       "      <td>0.6355</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>7526</td>\n",
       "      <td>0</td>\n",
       "      <td>7780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40363</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200075</td>\n",
       "      <td>26019033</td>\n",
       "      <td>7</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>4.5689</td>\n",
       "      <td>1.8752</td>\n",
       "      <td>1.1969</td>\n",
       "      <td>7.0792</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>7</td>\n",
       "      <td>38</td>\n",
       "      <td>3285</td>\n",
       "      <td>0</td>\n",
       "      <td>1722</td>\n",
       "      <td>0</td>\n",
       "      <td>2966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40364</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200075</td>\n",
       "      <td>26019034</td>\n",
       "      <td>8</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>2.7736</td>\n",
       "      <td>2.0573</td>\n",
       "      <td>0.3368</td>\n",
       "      <td>1.3647</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>50</td>\n",
       "      <td>595</td>\n",
       "      <td>13</td>\n",
       "      <td>989</td>\n",
       "      <td>0</td>\n",
       "      <td>332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40365</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200075</td>\n",
       "      <td>26019035</td>\n",
       "      <td>9</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>3.3177</td>\n",
       "      <td>2.2154</td>\n",
       "      <td>0.4671</td>\n",
       "      <td>2.4111</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>58</td>\n",
       "      <td>964</td>\n",
       "      <td>0</td>\n",
       "      <td>595</td>\n",
       "      <td>0</td>\n",
       "      <td>903</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40366</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200075</td>\n",
       "      <td>26019027</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>6.7850</td>\n",
       "      <td>23.4546</td>\n",
       "      <td>3.3173</td>\n",
       "      <td>11.7958</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>16</td>\n",
       "      <td>15</td>\n",
       "      <td>90</td>\n",
       "      <td>6010</td>\n",
       "      <td>11</td>\n",
       "      <td>16786</td>\n",
       "      <td>30</td>\n",
       "      <td>27461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40367</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200075</td>\n",
       "      <td>26019028</td>\n",
       "      <td>11</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>8.6193</td>\n",
       "      <td>17.0379</td>\n",
       "      <td>5.0670</td>\n",
       "      <td>15.4725</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>27</td>\n",
       "      <td>127</td>\n",
       "      <td>396</td>\n",
       "      <td>7136</td>\n",
       "      <td>5</td>\n",
       "      <td>40204</td>\n",
       "      <td>6</td>\n",
       "      <td>45022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>40368 rows × 71 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     时间     基站编号      小区编号  本地小区标识  上行可用的PRB个数  下行可用的PRB个数  \\\n",
       "0      2021-08-28 00:00  1200071  26019014       0         100         100   \n",
       "1      2021-08-28 00:00  1200071  26019015       1         100         100   \n",
       "2      2021-08-28 00:00  1200071  26019016       2         100         100   \n",
       "3      2021-08-28 00:00  1200071  26019023       3         100         100   \n",
       "4      2021-08-28 00:00  1200071  26019024       4         100         100   \n",
       "...                 ...      ...       ...     ...         ...         ...   \n",
       "40363  2021-09-25 23:00  1200075  26019033       7         100         100   \n",
       "40364  2021-09-25 23:00  1200075  26019034       8         100         100   \n",
       "40365  2021-09-25 23:00  1200075  26019035       9         100         100   \n",
       "40366  2021-09-25 23:00  1200075  26019027      10         100         100   \n",
       "40367  2021-09-25 23:00  1200075  26019028      11         100         100   \n",
       "\n",
       "       上行PhysicalResourceBlock被使用的平均个数  下行PhysicalResourceBlock被使用的平均个数  \\\n",
       "0                               6.4553                          31.5065   \n",
       "1                               8.8281                          21.5452   \n",
       "2                               5.5024                          11.9276   \n",
       "3                               3.1113                           0.9637   \n",
       "4                               2.6004                           1.0051   \n",
       "...                                ...                              ...   \n",
       "40363                           4.5689                           1.8752   \n",
       "40364                           2.7736                           2.0573   \n",
       "40365                           3.3177                           2.2154   \n",
       "40366                           6.7850                          23.4546   \n",
       "40367                           8.6193                          17.0379   \n",
       "\n",
       "       上行PUSCH的PhysicalResourceBlock被使用的平均个数  小区内的平均用户数  ...  \\\n",
       "0                                     2.1503    22.6341  ...   \n",
       "1                                     4.2220    19.1064  ...   \n",
       "2                                     1.8618    15.4729  ...   \n",
       "3                                     0.0077     0.0509  ...   \n",
       "4                                     0.1201     0.6355  ...   \n",
       "...                                      ...        ...  ...   \n",
       "40363                                 1.1969     7.0792  ...   \n",
       "40364                                 0.3368     1.3647  ...   \n",
       "40365                                 0.4671     2.4111  ...   \n",
       "40366                                 3.3173    11.7958  ...   \n",
       "40367                                 5.0670    15.4725  ...   \n",
       "\n",
       "       用户随机接入时TA值在区间11范围的接入次数  MR测量上报RSRP在Index0区间的次数  MR测量上报RSRP在Index1区间的次数  \\\n",
       "0                           0                       3                      16   \n",
       "1                           0                       2                       4   \n",
       "2                           0                       2                       4   \n",
       "3                           0                       0                       0   \n",
       "4                           0                       0                       1   \n",
       "...                       ...                     ...                     ...   \n",
       "40363                       0                       0                       5   \n",
       "40364                       0                       2                       8   \n",
       "40365                       0                       1                       2   \n",
       "40366                       0                       4                      16   \n",
       "40367                       0                      10                      27   \n",
       "\n",
       "       MR测量上报RSRP在Index2区间的次数  MR测量上报RSRP在Index3区间的次数  MR测量上报RSRP在Index4区间的次数  \\\n",
       "0                          17                     178                    9943   \n",
       "1                          21                     180                    8427   \n",
       "2                          48                     575                    6371   \n",
       "3                           0                       3                      31   \n",
       "4                           1                       9                     285   \n",
       "...                       ...                     ...                     ...   \n",
       "40363                       7                      38                    3285   \n",
       "40364                      10                      50                     595   \n",
       "40365                       3                      58                     964   \n",
       "40366                      15                      90                    6010   \n",
       "40367                     127                     396                    7136   \n",
       "\n",
       "       小区QCI为1的DRB业务PDCPSDU上行丢弃的总包数包  小区QCI为1的DRB业务PDCPSDU上行期望收到的总包数  \\\n",
       "0                                  0                            2218   \n",
       "1                                  0                            1510   \n",
       "2                                  0                            2030   \n",
       "3                                  0                               0   \n",
       "4                                  0                            7526   \n",
       "...                              ...                             ...   \n",
       "40363                              0                            1722   \n",
       "40364                             13                             989   \n",
       "40365                              0                             595   \n",
       "40366                             11                           16786   \n",
       "40367                              5                           40204   \n",
       "\n",
       "       小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数  小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数  \n",
       "0                                   0                            2179  \n",
       "1                                   0                            1423  \n",
       "2                                   0                            1919  \n",
       "3                                   0                               0  \n",
       "4                                   0                            7780  \n",
       "...                               ...                             ...  \n",
       "40363                               0                            2966  \n",
       "40364                               0                             332  \n",
       "40365                               0                             903  \n",
       "40366                              30                           27461  \n",
       "40367                               6                           45022  \n",
       "\n",
       "[40368 rows x 71 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=pd.read_excel('附件1：赛题A数据.xlsx','比赛数据-脱敏')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b9648878",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 40368 entries, 0 to 40367\n",
      "Data columns (total 71 columns):\n",
      " #   Column                                 Non-Null Count  Dtype  \n",
      "---  ------                                 --------------  -----  \n",
      " 0   时间                                     40368 non-null  object \n",
      " 1   基站编号                                   40368 non-null  int64  \n",
      " 2   小区编号                                   40368 non-null  int64  \n",
      " 3   本地小区标识                                 40368 non-null  int64  \n",
      " 4   上行可用的PRB个数                             40368 non-null  int64  \n",
      " 5   下行可用的PRB个数                             40368 non-null  int64  \n",
      " 6   上行PhysicalResourceBlock被使用的平均个数        40368 non-null  float64\n",
      " 7   下行PhysicalResourceBlock被使用的平均个数        40368 non-null  float64\n",
      " 8   上行PUSCH的PhysicalResourceBlock被使用的平均个数  40368 non-null  float64\n",
      " 9   小区内的平均用户数                              40368 non-null  float64\n",
      " 10  小区内的最大用户数                              40368 non-null  int64  \n",
      " 11  RRC连接建立完成次数                            40368 non-null  int64  \n",
      " 12  RRC连接请求次数（不包括重发）                       40368 non-null  int64  \n",
      " 13  ERAB建立成功总次数                            40368 non-null  int64  \n",
      " 14  ERAB建立尝试总次数                            40368 non-null  int64  \n",
      " 15  ERAB异常释放总次数                            40368 non-null  int64  \n",
      " 16  ERAB正常释放总次数                            40368 non-null  int64  \n",
      " 17  系统间切换出ERAB正常释放总次数                      40368 non-null  int64  \n",
      " 18  eNodeB内同频切换出成功次数                       40368 non-null  int64  \n",
      " 19  eNodeB间同频切换出成功次数                       40368 non-null  int64  \n",
      " 20  eNodeB内同频切换出执行次数                       40368 non-null  int64  \n",
      " 21  eNodeB间同频切换出执行次数                       40368 non-null  int64  \n",
      " 22  eNodeB内异频切换出成功次数                       40368 non-null  int64  \n",
      " 23  eNodeB间异频切换出成功次数                       40368 non-null  int64  \n",
      " 24  eNodeB内异频切换出执行次数                       40368 non-null  int64  \n",
      " 25  eNodeB间异频切换出执行次数                       40368 non-null  int64  \n",
      " 26  小区PDCP层所发送的下行数据的总吞吐量比特                 40368 non-null  int64  \n",
      " 27  使缓存为空的最后一个TTI所传的下行PDCP吞吐量比             40368 non-null  int64  \n",
      " 28  扣除使下行缓存为空的最后一个TTI之后的数传时                40368 non-null  int64  \n",
      " 29  小区PDCP层所接收到的上行数据的总吞吐量比特                40368 non-null  int64  \n",
      " 30  使UE缓存为空的最后一个TTI所传的上行PDCP吞吐量            40368 non-null  int64  \n",
      " 31  扣除使UE缓存为空的最后一个TTI之后的上行数传               40368 non-null  int64  \n",
      " 32  平均激活用户数                                40368 non-null  float64\n",
      " 33  最大激活用户数                                40368 non-null  int64  \n",
      " 34  空口上报全带宽CQI为0的次数                        40368 non-null  int64  \n",
      " 35  空口上报全带宽CQI为1的次数                        40368 non-null  int64  \n",
      " 36  空口上报全带宽CQI为2的次数                        40368 non-null  int64  \n",
      " 37  空口上报全带宽CQI为3的次数                        40368 non-null  int64  \n",
      " 38  空口上报全带宽CQI为4的次数                        40368 non-null  int64  \n",
      " 39  空口上报全带宽CQI为5的次数                        40368 non-null  int64  \n",
      " 40  空口上报全带宽CQI为6的次数                        40368 non-null  int64  \n",
      " 41  空口上报全带宽CQI为7的次数                        40368 non-null  int64  \n",
      " 42  空口上报全带宽CQI为8的次数                        40368 non-null  int64  \n",
      " 43  空口上报全带宽CQI为9的次数                        40368 non-null  int64  \n",
      " 44  空口上报全带宽CQI为10的次数                       40368 non-null  int64  \n",
      " 45  空口上报全带宽CQI为11的次数                       40368 non-null  int64  \n",
      " 46  空口上报全带宽CQI为12的次数                       40368 non-null  int64  \n",
      " 47  空口上报全带宽CQI为13的次数                       40368 non-null  int64  \n",
      " 48  空口上报全带宽CQI为14的次数                       40368 non-null  int64  \n",
      " 49  空口上报全带宽CQI为15的次数                       40368 non-null  int64  \n",
      " 50  用户随机接入时TA值在区间0范围的接入次数                  40368 non-null  int64  \n",
      " 51  用户随机接入时TA值在区间1范围的接入次数                  40368 non-null  int64  \n",
      " 52  用户随机接入时TA值在区间2范围的接入次数                  40368 non-null  int64  \n",
      " 53  用户随机接入时TA值在区间3范围的接入次数                  40368 non-null  int64  \n",
      " 54  用户随机接入时TA值在区间4范围的接入次数                  40368 non-null  int64  \n",
      " 55  用户随机接入时TA值在区间5范围的接入次数                  40368 non-null  int64  \n",
      " 56  用户随机接入时TA值在区间6范围的接入次数                  40368 non-null  int64  \n",
      " 57  用户随机接入时TA值在区间7范围的接入次数                  40368 non-null  int64  \n",
      " 58  用户随机接入时TA值在区间8范围的接入次数                  40368 non-null  int64  \n",
      " 59  用户随机接入时TA值在区间9范围的接入次数                  40368 non-null  int64  \n",
      " 60  用户随机接入时TA值在区间10范围的接入次数                 40368 non-null  int64  \n",
      " 61  用户随机接入时TA值在区间11范围的接入次数                 40368 non-null  int64  \n",
      " 62  MR测量上报RSRP在Index0区间的次数                 40368 non-null  int64  \n",
      " 63  MR测量上报RSRP在Index1区间的次数                 40368 non-null  int64  \n",
      " 64  MR测量上报RSRP在Index2区间的次数                 40368 non-null  int64  \n",
      " 65  MR测量上报RSRP在Index3区间的次数                 40368 non-null  int64  \n",
      " 66  MR测量上报RSRP在Index4区间的次数                 40368 non-null  int64  \n",
      " 67  小区QCI为1的DRB业务PDCPSDU上行丢弃的总包数包          40368 non-null  int64  \n",
      " 68  小区QCI为1的DRB业务PDCPSDU上行期望收到的总包数         40368 non-null  int64  \n",
      " 69  小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数         40368 non-null  int64  \n",
      " 70  小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数         40368 non-null  int64  \n",
      "dtypes: float64(5), int64(65), object(1)\n",
      "memory usage: 21.9+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "af33fde6",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data.sort_values(by=['时间'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "2cd75ddc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "plt.plot(data.时间,data.drop('时间',axis=1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "804717a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">小区编号</th>\n",
       "      <th colspan=\"2\" halign=\"left\">本地小区标识</th>\n",
       "      <th>...</th>\n",
       "      <th colspan=\"2\" halign=\"left\">小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数</th>\n",
       "      <th colspan=\"8\" halign=\"left\">小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>...</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>基站编号</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1200071</th>\n",
       "      <td>8352.0</td>\n",
       "      <td>2.601902e+07</td>\n",
       "      <td>16.558131</td>\n",
       "      <td>26019009.0</td>\n",
       "      <td>26019011.75</td>\n",
       "      <td>26019014.5</td>\n",
       "      <td>26019023.25</td>\n",
       "      <td>26019058.0</td>\n",
       "      <td>8352.0</td>\n",
       "      <td>5.583333</td>\n",
       "      <td>...</td>\n",
       "      <td>14.0</td>\n",
       "      <td>2536.0</td>\n",
       "      <td>8352.0</td>\n",
       "      <td>54475.796336</td>\n",
       "      <td>74811.573876</td>\n",
       "      <td>0.0</td>\n",
       "      <td>905.75</td>\n",
       "      <td>18257.0</td>\n",
       "      <td>85456.50</td>\n",
       "      <td>513540.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1200072</th>\n",
       "      <td>8352.0</td>\n",
       "      <td>2.601902e+07</td>\n",
       "      <td>10.468501</td>\n",
       "      <td>26019004.0</td>\n",
       "      <td>26019006.75</td>\n",
       "      <td>26019020.5</td>\n",
       "      <td>26019026.25</td>\n",
       "      <td>26019032.0</td>\n",
       "      <td>8352.0</td>\n",
       "      <td>9.833333</td>\n",
       "      <td>...</td>\n",
       "      <td>33.0</td>\n",
       "      <td>2354.0</td>\n",
       "      <td>8352.0</td>\n",
       "      <td>77159.990182</td>\n",
       "      <td>109219.451042</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3868.75</td>\n",
       "      <td>32471.5</td>\n",
       "      <td>105947.50</td>\n",
       "      <td>816022.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1200073</th>\n",
       "      <td>11832.0</td>\n",
       "      <td>2.601904e+07</td>\n",
       "      <td>18.202256</td>\n",
       "      <td>26019001.0</td>\n",
       "      <td>26019037.00</td>\n",
       "      <td>26019046.0</td>\n",
       "      <td>26019052.00</td>\n",
       "      <td>26019056.0</td>\n",
       "      <td>11832.0</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>8.0</td>\n",
       "      <td>757.0</td>\n",
       "      <td>11832.0</td>\n",
       "      <td>38888.474814</td>\n",
       "      <td>55655.526698</td>\n",
       "      <td>0.0</td>\n",
       "      <td>238.75</td>\n",
       "      <td>13851.0</td>\n",
       "      <td>56105.50</td>\n",
       "      <td>375764.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1200074</th>\n",
       "      <td>5568.0</td>\n",
       "      <td>2.601903e+07</td>\n",
       "      <td>11.684371</td>\n",
       "      <td>26019017.0</td>\n",
       "      <td>26019018.75</td>\n",
       "      <td>26019040.5</td>\n",
       "      <td>26019042.25</td>\n",
       "      <td>26019044.0</td>\n",
       "      <td>5568.0</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>12.0</td>\n",
       "      <td>651.0</td>\n",
       "      <td>5568.0</td>\n",
       "      <td>44951.696839</td>\n",
       "      <td>80344.293090</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1349.5</td>\n",
       "      <td>57096.75</td>\n",
       "      <td>492791.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1200075</th>\n",
       "      <td>6264.0</td>\n",
       "      <td>2.601903e+07</td>\n",
       "      <td>8.526603</td>\n",
       "      <td>26019026.0</td>\n",
       "      <td>26019028.00</td>\n",
       "      <td>26019033.0</td>\n",
       "      <td>26019035.00</td>\n",
       "      <td>26019050.0</td>\n",
       "      <td>6264.0</td>\n",
       "      <td>6.222222</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2173.0</td>\n",
       "      <td>6264.0</td>\n",
       "      <td>33665.055556</td>\n",
       "      <td>63870.983247</td>\n",
       "      <td>0.0</td>\n",
       "      <td>522.00</td>\n",
       "      <td>4489.5</td>\n",
       "      <td>25787.25</td>\n",
       "      <td>467898.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 552 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            小区编号                                                    \\\n",
       "           count          mean        std         min          25%   \n",
       "基站编号                                                                 \n",
       "1200071   8352.0  2.601902e+07  16.558131  26019009.0  26019011.75   \n",
       "1200072   8352.0  2.601902e+07  10.468501  26019004.0  26019006.75   \n",
       "1200073  11832.0  2.601904e+07  18.202256  26019001.0  26019037.00   \n",
       "1200074   5568.0  2.601903e+07  11.684371  26019017.0  26019018.75   \n",
       "1200075   6264.0  2.601903e+07   8.526603  26019026.0  26019028.00   \n",
       "\n",
       "                                               本地小区标识            ...  \\\n",
       "                50%          75%         max    count      mean  ...   \n",
       "基站编号                                                             ...   \n",
       "1200071  26019014.5  26019023.25  26019058.0   8352.0  5.583333  ...   \n",
       "1200072  26019020.5  26019026.25  26019032.0   8352.0  9.833333  ...   \n",
       "1200073  26019046.0  26019052.00  26019056.0  11832.0  8.000000  ...   \n",
       "1200074  26019040.5  26019042.25  26019044.0   5568.0  4.500000  ...   \n",
       "1200075  26019033.0  26019035.00  26019050.0   6264.0  6.222222  ...   \n",
       "\n",
       "        小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数         小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数  \\\n",
       "                                   75%     max                          count   \n",
       "基站编号                                                                            \n",
       "1200071                           14.0  2536.0                         8352.0   \n",
       "1200072                           33.0  2354.0                         8352.0   \n",
       "1200073                            8.0   757.0                        11832.0   \n",
       "1200074                           12.0   651.0                         5568.0   \n",
       "1200075                           10.0  2173.0                         6264.0   \n",
       "\n",
       "                                                                        \\\n",
       "                 mean            std  min      25%      50%        75%   \n",
       "基站编号                                                                     \n",
       "1200071  54475.796336   74811.573876  0.0   905.75  18257.0   85456.50   \n",
       "1200072  77159.990182  109219.451042  0.0  3868.75  32471.5  105947.50   \n",
       "1200073  38888.474814   55655.526698  0.0   238.75  13851.0   56105.50   \n",
       "1200074  44951.696839   80344.293090  0.0     0.00   1349.5   57096.75   \n",
       "1200075  33665.055556   63870.983247  0.0   522.00   4489.5   25787.25   \n",
       "\n",
       "                   \n",
       "              max  \n",
       "基站编号               \n",
       "1200071  513540.0  \n",
       "1200072  816022.0  \n",
       "1200073  375764.0  \n",
       "1200074  492791.0  \n",
       "1200075  467898.0  \n",
       "\n",
       "[5 rows x 552 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grpdata=data.groupby(['基站编号'])\n",
    "grpdata.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2398545f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>时间</th>\n",
       "      <th>基站编号</th>\n",
       "      <th>小区编号</th>\n",
       "      <th>本地小区标识</th>\n",
       "      <th>上行可用的PRB个数</th>\n",
       "      <th>下行可用的PRB个数</th>\n",
       "      <th>上行PhysicalResourceBlock被使用的平均个数</th>\n",
       "      <th>下行PhysicalResourceBlock被使用的平均个数</th>\n",
       "      <th>上行PUSCH的PhysicalResourceBlock被使用的平均个数</th>\n",
       "      <th>小区内的平均用户数</th>\n",
       "      <th>...</th>\n",
       "      <th>用户随机接入时TA值在区间11范围的接入次数</th>\n",
       "      <th>MR测量上报RSRP在Index0区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index1区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index2区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index3区间的次数</th>\n",
       "      <th>MR测量上报RSRP在Index4区间的次数</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU上行丢弃的总包数包</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU上行期望收到的总包数</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数</th>\n",
       "      <th>小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019014</td>\n",
       "      <td>0</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>6.4553</td>\n",
       "      <td>31.5065</td>\n",
       "      <td>2.1503</td>\n",
       "      <td>22.6341</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>178</td>\n",
       "      <td>9943</td>\n",
       "      <td>0</td>\n",
       "      <td>2218</td>\n",
       "      <td>0</td>\n",
       "      <td>2179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019015</td>\n",
       "      <td>1</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>8.8281</td>\n",
       "      <td>21.5452</td>\n",
       "      <td>4.2220</td>\n",
       "      <td>19.1064</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>21</td>\n",
       "      <td>180</td>\n",
       "      <td>8427</td>\n",
       "      <td>0</td>\n",
       "      <td>1510</td>\n",
       "      <td>0</td>\n",
       "      <td>1423</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019016</td>\n",
       "      <td>2</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>5.5024</td>\n",
       "      <td>11.9276</td>\n",
       "      <td>1.8618</td>\n",
       "      <td>15.4729</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>48</td>\n",
       "      <td>575</td>\n",
       "      <td>6371</td>\n",
       "      <td>0</td>\n",
       "      <td>2030</td>\n",
       "      <td>0</td>\n",
       "      <td>1919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019023</td>\n",
       "      <td>3</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>3.1113</td>\n",
       "      <td>0.9637</td>\n",
       "      <td>0.0077</td>\n",
       "      <td>0.0509</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2021-08-28 00:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019024</td>\n",
       "      <td>4</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>2.6004</td>\n",
       "      <td>1.0051</td>\n",
       "      <td>0.1201</td>\n",
       "      <td>0.6355</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>285</td>\n",
       "      <td>0</td>\n",
       "      <td>7526</td>\n",
       "      <td>0</td>\n",
       "      <td>7780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40317</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019012</td>\n",
       "      <td>7</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>7.9223</td>\n",
       "      <td>13.5207</td>\n",
       "      <td>4.4914</td>\n",
       "      <td>9.1791</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>6</td>\n",
       "      <td>43</td>\n",
       "      <td>222</td>\n",
       "      <td>4086</td>\n",
       "      <td>0</td>\n",
       "      <td>4126</td>\n",
       "      <td>3</td>\n",
       "      <td>6141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40318</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019013</td>\n",
       "      <td>8</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>11.9420</td>\n",
       "      <td>51.0373</td>\n",
       "      <td>7.9622</td>\n",
       "      <td>27.2408</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>24</td>\n",
       "      <td>119</td>\n",
       "      <td>12643</td>\n",
       "      <td>1</td>\n",
       "      <td>17538</td>\n",
       "      <td>1</td>\n",
       "      <td>25339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40319</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019057</td>\n",
       "      <td>9</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>2.8246</td>\n",
       "      <td>6.4060</td>\n",
       "      <td>0.1743</td>\n",
       "      <td>1.2758</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>31</td>\n",
       "      <td>529</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40320</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019058</td>\n",
       "      <td>10</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>3.0991</td>\n",
       "      <td>3.2024</td>\n",
       "      <td>0.3961</td>\n",
       "      <td>1.9800</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>37</td>\n",
       "      <td>21</td>\n",
       "      <td>118</td>\n",
       "      <td>805</td>\n",
       "      <td>0</td>\n",
       "      <td>565</td>\n",
       "      <td>4</td>\n",
       "      <td>399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40321</th>\n",
       "      <td>2021-09-25 23:00</td>\n",
       "      <td>1200071</td>\n",
       "      <td>26019009</td>\n",
       "      <td>12</td>\n",
       "      <td>100</td>\n",
       "      <td>100</td>\n",
       "      <td>11.0254</td>\n",
       "      <td>22.3106</td>\n",
       "      <td>7.5460</td>\n",
       "      <td>28.2222</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>10</td>\n",
       "      <td>75</td>\n",
       "      <td>122</td>\n",
       "      <td>12662</td>\n",
       "      <td>0</td>\n",
       "      <td>12864</td>\n",
       "      <td>2</td>\n",
       "      <td>10493</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8352 rows × 71 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     时间     基站编号      小区编号  本地小区标识  上行可用的PRB个数  下行可用的PRB个数  \\\n",
       "0      2021-08-28 00:00  1200071  26019014       0         100         100   \n",
       "1      2021-08-28 00:00  1200071  26019015       1         100         100   \n",
       "2      2021-08-28 00:00  1200071  26019016       2         100         100   \n",
       "3      2021-08-28 00:00  1200071  26019023       3         100         100   \n",
       "4      2021-08-28 00:00  1200071  26019024       4         100         100   \n",
       "...                 ...      ...       ...     ...         ...         ...   \n",
       "40317  2021-09-25 23:00  1200071  26019012       7         100         100   \n",
       "40318  2021-09-25 23:00  1200071  26019013       8         100         100   \n",
       "40319  2021-09-25 23:00  1200071  26019057       9         100         100   \n",
       "40320  2021-09-25 23:00  1200071  26019058      10         100         100   \n",
       "40321  2021-09-25 23:00  1200071  26019009      12         100         100   \n",
       "\n",
       "       上行PhysicalResourceBlock被使用的平均个数  下行PhysicalResourceBlock被使用的平均个数  \\\n",
       "0                               6.4553                          31.5065   \n",
       "1                               8.8281                          21.5452   \n",
       "2                               5.5024                          11.9276   \n",
       "3                               3.1113                           0.9637   \n",
       "4                               2.6004                           1.0051   \n",
       "...                                ...                              ...   \n",
       "40317                           7.9223                          13.5207   \n",
       "40318                          11.9420                          51.0373   \n",
       "40319                           2.8246                           6.4060   \n",
       "40320                           3.0991                           3.2024   \n",
       "40321                          11.0254                          22.3106   \n",
       "\n",
       "       上行PUSCH的PhysicalResourceBlock被使用的平均个数  小区内的平均用户数  ...  \\\n",
       "0                                     2.1503    22.6341  ...   \n",
       "1                                     4.2220    19.1064  ...   \n",
       "2                                     1.8618    15.4729  ...   \n",
       "3                                     0.0077     0.0509  ...   \n",
       "4                                     0.1201     0.6355  ...   \n",
       "...                                      ...        ...  ...   \n",
       "40317                                 4.4914     9.1791  ...   \n",
       "40318                                 7.9622    27.2408  ...   \n",
       "40319                                 0.1743     1.2758  ...   \n",
       "40320                                 0.3961     1.9800  ...   \n",
       "40321                                 7.5460    28.2222  ...   \n",
       "\n",
       "       用户随机接入时TA值在区间11范围的接入次数  MR测量上报RSRP在Index0区间的次数  MR测量上报RSRP在Index1区间的次数  \\\n",
       "0                           0                       3                      16   \n",
       "1                           0                       2                       4   \n",
       "2                           0                       2                       4   \n",
       "3                           0                       0                       0   \n",
       "4                           0                       0                       1   \n",
       "...                       ...                     ...                     ...   \n",
       "40317                       0                       3                       6   \n",
       "40318                       0                       2                       6   \n",
       "40319                       0                       0                       0   \n",
       "40320                       0                       3                      37   \n",
       "40321                       0                       8                      10   \n",
       "\n",
       "       MR测量上报RSRP在Index2区间的次数  MR测量上报RSRP在Index3区间的次数  MR测量上报RSRP在Index4区间的次数  \\\n",
       "0                          17                     178                    9943   \n",
       "1                          21                     180                    8427   \n",
       "2                          48                     575                    6371   \n",
       "3                           0                       3                      31   \n",
       "4                           1                       9                     285   \n",
       "...                       ...                     ...                     ...   \n",
       "40317                      43                     222                    4086   \n",
       "40318                      24                     119                   12643   \n",
       "40319                       0                      31                     529   \n",
       "40320                      21                     118                     805   \n",
       "40321                      75                     122                   12662   \n",
       "\n",
       "       小区QCI为1的DRB业务PDCPSDU上行丢弃的总包数包  小区QCI为1的DRB业务PDCPSDU上行期望收到的总包数  \\\n",
       "0                                  0                            2218   \n",
       "1                                  0                            1510   \n",
       "2                                  0                            2030   \n",
       "3                                  0                               0   \n",
       "4                                  0                            7526   \n",
       "...                              ...                             ...   \n",
       "40317                              0                            4126   \n",
       "40318                              1                           17538   \n",
       "40319                              0                               0   \n",
       "40320                              0                             565   \n",
       "40321                              0                           12864   \n",
       "\n",
       "       小区QCI为1的DRB业务PDCPSDU下行空口丢弃的总包数  小区QCI为1的DRB业务PDCPSDU下行空口发送的总包数  \n",
       "0                                   0                            2179  \n",
       "1                                   0                            1423  \n",
       "2                                   0                            1919  \n",
       "3                                   0                               0  \n",
       "4                                   0                            7780  \n",
       "...                               ...                             ...  \n",
       "40317                               3                            6141  \n",
       "40318                               1                           25339  \n",
       "40319                               0                               0  \n",
       "40320                               4                             399  \n",
       "40321                               2                           10493  \n",
       "\n",
       "[8352 rows x 71 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "station=[]\n",
    "for i in range(5):\n",
    "    station.append(data[data.基站编号==1200071+i])\n",
    "#     print(station[i].head())\n",
    "station[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "eca36099",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[['2021-08-28 00:00' 1200071 26019014 ... 0 2218 0]\n",
      " ['2021-08-28 00:00' 1200071 26019015 ... 0 1510 0]\n",
      " ['2021-08-28 00:00' 1200071 26019016 ... 0 2030 0]\n",
      " ...\n",
      " ['2021-08-28 08:00' 1200071 26019015 ... 3 9901 13]\n",
      " ['2021-08-28 08:00' 1200071 26019016 ... 0 43039 8]\n",
      " ['2021-08-28 08:00' 1200071 26019023 ... 0 4687 0]]\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 7200x7200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "均方误差(MSE)：1.480878675707139e+19\n",
      "根均方误差(RMSE)：3848218647.2537384\n",
      "测试集R^2：0.4475966478367582\n"
     ]
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from sklearn.metrics import precision_score\n",
    "\n",
    "# 导入数据集，定义自变量、因变量\n",
    "dataset = station[0].head(100)\n",
    "dataset=dataset.drop()\n",
    "X = dataset.iloc[:, :-1].values\n",
    "y = dataset.iloc[:, [9,26,28]].values\n",
    "print(X)\n",
    "\n",
    "# 对于分类字符串进行编码，LabelEncoder文本变数值，OneHotEncoder数值变OneHot编码\n",
    "from sklearn.preprocessing import LabelEncoder, OneHotEncoder\n",
    "labelencoder_X = LabelEncoder()\n",
    "X[:,3] = labelencoder_X.fit_transform(X[:,3])\n",
    "onehotencoder = OneHotEncoder()\n",
    "X = onehotencoder.fit_transform(X).toarray()\n",
    "#避免虚拟变量陷阱\n",
    "X = X[:,1:]\n",
    "# 分离训练集与测试集 \n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)\n",
    "\n",
    "# 定义回归器，模型拟合\n",
    "from sklearn.linear_model import LinearRegression\n",
    "regressor = LinearRegression()\n",
    "regressor.fit(X_train, y_train)\n",
    "\n",
    "# 预测且查看pred与test数据\n",
    "y_pred = regressor.predict(X_test)\n",
    "np.set_printoptions(precision=2)#查看小数点精确度设定\n",
    "#np.concatenate数组拼接工具，首先转化为10*1维数组，进行纵向拼接查看\n",
    "# print(np.concatenate((y_pred.reshape(len(y_pred),1), y_test.reshape(len(y_test),1)),1))\n",
    "\n",
    "# 查看相关矩阵，correlation matrix, 分析变量关系\n",
    "corrmat = dataset.corr()\n",
    "plt.figure(figsize=(100,100))\n",
    "plt.rcParams['font.sans-serif']=['Arial Unicode MS']\n",
    "sns.set(font=\"Arial Unicode MS\")\n",
    "sns.heatmap(corrmat, vmax=.8, square=True)\n",
    "\n",
    "plt.show()\n",
    "\n",
    "#模型评估\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "print(f\"均方误差(MSE)：{mean_squared_error(y_pred, y_test)}\")\n",
    "print(f\"根均方误差(RMSE)：{np.sqrt(mean_squared_error(y_pred, y_test))}\")\n",
    "print(f\"测试集R^2：{r2_score(y_test, y_pred)}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b4f104bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(8352, 71)\n",
      "(8352, 71)\n",
      "(11832, 71)\n",
      "(5568, 71)\n",
      "(6264, 71)\n",
      "40368\n"
     ]
    }
   ],
   "source": [
    "# sum=0\n",
    "# for i in range(5):\n",
    "#     print(station[i].shape)\n",
    "#     sum+=station[i].shape[0]\n",
    "# print(sum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4fc5991d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Int64Index([    0,    31,    32,    33,    34,    35,    36,    37,    38,\n",
      "               39,\n",
      "            ...\n",
      "            40328, 40329, 40330, 40331, 40332, 40333, 40334, 40335, 40322,\n",
      "            40367],\n",
      "           dtype='int64', length=40368)\n"
     ]
    }
   ],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
